ABSTRACT A total of 39 healthy adolescents and 45 adolescents with schizophrenic disorders (mean age 12.3 years) were examined to study the EEG structural synchrony as reflecting temporal synchronization of the operational activity of neuronal networks. A significant decrease in the EEG structural synchrony was observed in the adolescents with schizophrenic disorders as compared to the healthy adolescents. The decrease was detected predominantly in the interhemispheric pairs of EEG derivations, as well as in the pairs related to the frontal, temporal (predominantly on the left), and right parietocentral regions. The findings provide evidence in favor of Friston’s hypothesis of disintegration of cortical electrical activity in schizophrenia and extend the hypothesis in that it is the operational synchrony of cortical activity that might suffer first in schizophrenia.

[Show abstract][Hide abstract]ABSTRACT:
Children aged 5–7 years with early childhood autism were found to have more marked right-sided predominance of alpha-rhythm spectral power both in baseline conditions and on cognitive loading (counting), along with a decreased level of alpha rhythm power than normal children. The spectral power of the fast rhythms increased from baseline on cognitive loading in healthy children. In early childhood autism, the spectral power of the gamma rhythm in baseline conditions was greater than that in healthy children. On cognitive loading, the spectral power of the fast rhythms changed to a lesser extent than in healthy children. D creased alpha rhythm power in children with autism may be a predictor for the transition from autism to schizophrenia (with both positive and negative symptomatology). The increased spectral power of the fast rhythms in baseline conditions observed here in children with early childhood autism is characteristic of schizophrenia with positive symptomatology, while the decreased reactivity of fast rhythms in response to cognitive loading seen here in patients has been described for schizophrenia with negative symptomatology.

[Show abstract][Hide abstract]ABSTRACT:
Concepts of space and time are widely developed in physics. However, there is a considerable lack of biologically plausible theoretical frameworks that can demonstrate how space and time dimensions are implemented in the activity of the most complex life-system - the brain with a mind. Brain activity is organized both temporally and spatially, thus representing space-time in the brain. Critical analysis of recent research on the space-time organization of the brain's activity pointed to the existence of so-called operational space-time in the brain. This space-time is limited to the execution of brain operations of differing complexity. During each such brain operation a particular short-term spatio-temporal pattern of integrated activity of different brain areas emerges within related operational space-time. At the same time, to have a fully functional human brain one needs to have a subjective mental experience. Current research on the subjective mental experience offers detailed analysis of space-time organization of the mind. According to this research, subjective mental experience (subjective virtual world) has definitive spatial and temporal properties similar to many physical phenomena. Based on systematic review of the propositions and tenets of brain and mind space-time descriptions, our aim in this review essay is to explore the relations between the two. To be precise, we would like to discuss the hypothesis that via the brain operational space-time the mind subjective space-time is connected to otherwise distant physical space-time reality.

[Show abstract][Hide abstract]ABSTRACT:
In today’s scenario, more and more people are required to travel back and forth to various places. With the increasing vehicular population and their movements on the roads, accidents are also steadily increasing. It has become a nightmare for the authorities to prevent /reduce such fatal accidents on the roads. But the authorities’ efforts are in vain. It is shocking to know the study results that around 50% of the road accidents are owing to drunken driving all over the world[1][2]. Any mechanism or device to reduce such deaths will be of great help. Drunken driving and its subsequent catastrophe can be avoided by monitoring the EEG of the driver. The power of the EEG signal in frontal region decreases with the increase in the amount of alcohol intake, and the power of the EEG signal in central, occipital region increases. Therefore, power spectral density can be used as a parameter to differentiate EEG of alcoholic from non- alcoholic, thereby reducing drunken driving. Results are presented to support this approach.

Data provided are for informational purposes only. Although carefully collected, accuracy cannot be guaranteed.
The impact factor represents a rough estimation of the journal's impact factor and does not reflect the actual
current impact factor.
Publisher conditions are provided by RoMEO. Differing provisions from the publisher's actual policy or licence
agreement may be applicable.

Schizophrenia falls into the small category of dis-eases that impair the total psychic activity rather thanparticular brain systems and functions. It is not surpris-ing that researchers have long been interested in theintegrative activity of the human brain in schizophre-nia. They have reported considerable data on histologi-cal and physiological changes in the human brain, pro-viding evidence for disturbance of interrelationshipsand functional association between different parts ofthe brain at different stages of schizophrenia [1–3]. Themost conspicuous data have been obtained for the brainelectrical activity [4–10]. Based on these data, ahypothesis of disintegration of cortical functions (thedisconnection hypothesis) has been advanced [11] toexplain the schizophrenic disorders [11–13].In EEG studies, spectral and correlation analyses area common method for investigating the integrativeactivity of the human brain, yielding evidence for theimpairment of local and distant synchronies of neu-ronal networks in schizophrenia [4, 5, 7, 8, 14]. How-ever, a number of limitations typical of spectral meth-ods, specifically, of the coherence function [7, 15–17],have motivated the development of new techniques toexamine the interdependences of EEG paired timeseries data in schizophrenia, including nonlinear inter-dependence [9], mutual information transmission mea-sure [18], and phase locking [10], which reflect nonlin-ear and, in the last case, also in-phase components ofthe interdependence of cortical electrical processes.The results of the above studies are also in line withFriston’s hypothesis of disintegration of neuronal net-works in schizophrenia [11].Yet, cortical bioelectrical processes associated withontological nonstationarity of the EEG signal [19–21]are not covered by the traditional or new methods ofquantitative analysis of EEG spatiotemporal correla-tions.EEG nonstationarity implies that the EEG signalconsists of quasi-stationary segments that reflect thechanges in metastable states of the brain on differenttime scales [20, 21], from microstates, with a durationof no more than several seconds [15, 22], to mac-rostates, with a duration of tens or hundreds of minutes[23]. This concept of EEG nonstationarity provides ameans for obtaining new insights into the cooperationof cortical structures. For this purpose, it is possible toestimate the EEG structural synchrony [15], i.e., thetemporal synchronization of intersegmentary transi-tions between different EEG channels. Estimation ofthe spatiotemporal synchronization of local metastablestates of neuronal networks appears to be a new mea-sure of the integrative activity of the human brain.The functional importance of the EEG structuralsynchrony and segment characteristics has beendescribed in a series of our works performed in severallaboratories and with several cognitive and pharmaco-logical paradigms [24–27]. In our previous work [28],changes in quasi-stationary segments of the EEG activity were detected in adolescents with schizo-phrenic disorders.

α

The objective of the present work was to analyze thedisease-related changes in structural synchrony of theEEG α activity in adolescents with schizophrenic dis-orders.

Abstractyears) were examined to study the EEG structural synchrony as reflecting temporal synchronization of the oper-ational activity of neuronal networks. A significant decrease in the EEG structural synchrony was observed inthe adolescents with schizophrenic disorders as compared to the healthy adolescents. The decrease was detectedpredominantly in the interhemispheric pairs of EEG derivations, as well as in the pairs related to the frontal,temporal (predominantly on the left), and right parietocentral regions. The findings provide evidence in favorof Friston’s hypothesis of disintegration of cortical electrical activity in schizophrenia and extend the hypothesisin that it is the operational synchrony of cortical activity that might suffer first in schizophrenia.

—A total of 39 healthy adolescents and 45 adolescents with schizophrenic disorders (mean age 12.3

Page 2

256

HUMAN PHYSIOLOGY

Vol. 31

No. 3

2005

BORISOV

et al

.

METHODSThe study involved 45 boys with schizophrenic dis-orders (infant schizophrenia and schizotypical andschizoaffective disorders (F20, F21, and F25 accordingto the ICD-10)) with similar symptoms. The diagnosesof all patients were confirmed by specialists of theMental Health Research Center (MHRC). None of theenrolled patients received chemotherapy during theexamination at the MHRC. The age of the patients var-ied from 10 years and 8 months to 14 years. The controlgroup included 39 healthy schoolboys aged from 11years to 13 years and 9 months. The mean age in bothgroups was 12 years and 3 months.The EEG was recorded in wakeful relaxed adoles-cents with the eyes closed from 16 electrodes, whichwere placed according to the international 10–20 sys-tem at O1, O2, P3, P4, Pz, TF4, F7, and F8 and monopolarly referenced to coupledear electrodes. The EEG recordings were analyzed witha sampling rate of 128 samples per second, and onlyartifact-free EEG segments were used for analysis.Analyzing the EEG structural synchrony, we usedthe SECTION 0.1 technology [24, 29] to perform EEGadaptive segmentation in order to identify quasi-sta-tionary segments of the α activity. Thereafter, the indexof structural synchrony (ISS) of the EEG [15, 29] wascalculated using the JUMPSYN 0.1 technology as

5

,

T

6

,

C

3

,

C

4

,

Cz

,

T

3

,

T

4

,

F

3

,

where coincidences of segment boundaries between two EEGderivations provided that the derivations are indepen-dent, Pe is the observed frequency of coincidences ofsegment boundaries between the two EEG derivations,and m is the mean error of PtAs can be seen from the formula, the ISS shows theextent of synchrony of the boundaries of quasi-station-ary segments, free from random coincidences, for agiven pair of derivations.The quasi-stationary segments of the EEG are supposed to reflect changes in local cortical neu-ronal ensembles [24, 25]; therefore, the ISS shows theextent of temporal synchronization of integration ordisintegration events in local neuronal ensembles forpairs of different EEG derivations.For the 120 possible combinations of the 16 EEGderivations, 120 ISS values were calculated. To deter-mine the ISS confidence interval (the stochastic level)giving an error probability of no more than 5% for theconclusion of a nonrandom nature of the structural syn-chrony for a given pair of derivations, a numericalexperiment according to the Monte Carlo techniquewas performed with 500 iterations.The ISS values calculated for each pair of deriva-tions were averaged for each group. The total syn-chrony, i.e., the mean ISS for all derivations, and the

Pt

is the theoretically predicted frequency of

.

α

activityISSPe----------------- -,Pt–m=

group synchrony for certain sets of derivation pairs,including left hemispheric (F3, and F7), right hemispheric (F4, and F8), frontal (F3, F4, C3, Cz, and C4), parietocentral (C3, C4, and Cz), posterior (T6), and symmetrical bilateral (pairs T6, T3–T4, C3–C4, F3–F4, and F7–F8) derivations, werecalculated separately for the control and test groups.The paired Wilcoxon t-test was used to estimate thesignificance of differences in the total and group syn-chronies between the control and test groups.Along with the group synchrony analysis, a detailedanalysis of the ISS values was performed with regard tothe ISS stochastic level and the distance between theelectrodes for a given pair of derivations. The Mann–Whitney U-test was used to compare ISS valuesexceeding the stochastic level in at least one of thegroups under study.

O

1O, and P31, O

,

P,

3P

,

Pz, F8P4, P

,

T,

5T

,

T,

3

,

C, C

34

, , , , , and, T5–

CzCzTT

,,,,

2

4

Pz), central (, Pz, T, P4, O1–O2

6

T

4

F

7

TT

33

44

,

5Pz, P

,

T

6

, TP

O

2

3

, –

5

3

4

RESULTSComparison of the ISS values averaged for the 120pairs for the control and test groups showed that thisindex was significantly lower in the adolescents withschizophrenic disorders (control group, 2.03 ± 0.19;test group, 1.67 ± 0.17 (M ± m)).Analysis of the group synchrony, i.e., ISS valuesaveraged for various sets of EEG derivations, revealeda decrease in this parameter for most sets of EEG deri-vation pairs (left hemispheric, right hemispheric, pari-etocentral, posterior, and bilateral) in the test group(Fig. 1). The differences in the ISS were nonsignificantonly for the frontal and central pairs of the EEG deriva-tions, although they showed a trend common to allgroups of derivations.We concluded that the level of EEG structural syn-chrony in the adolescents with schizophrenic disorderswas generally lower than in the healthy subjects.The question arises as to whether a decrease in theISS for the above pairs of derivations in the test groupis indicative of a regular trend equally typical of eachderivation pair or the ISS demonstrates different dis-ease-related trends for different pairs of derivations. Toanswer this question, we analyzed in detail the ISS val-ues for each pair of EEG derivations.The topographic patterns of the ISS calculated foreach of the 120 derivation pairs with regard to the sto-chastic level and for both the control and the test groupsare given in Fig. 2. The ISS considerably exceeded thestochastic level in many pairs of EEG derivations,thereby evidencing a nonrandom character of coinci-dences of intersegment transitions in the correspondingpairs of EEG derivations.When analyzing the differences in ISS between thecontrol and the test groups, we were interested in com-paring the above pairs, in particular, the topographicdistribution of these pairs in each group.

Page 3

HUMAN PHYSIOLOGY Vol. 31 No. 3 2005ANALYSIS OF EEG STRUCTURAL SYNCHRONY IN ADOLESCENTS257*******43210LefthemisphericRighthemisphericFrontalCentralParietocentralPosterior BilateralISSFig. 1. ISS values averaged for different pairs of derivations in the control (light columns) and test (dark columns) groups. Abscissa,pairs of derivations. Differences in group synchrony indices were significant at (*) P < 0.05 and (**) P < 0.001.*************************************397531–1–371115 192327 3135 39434751 5559 6367717579838791 9599103107111 115119ISSFig. 2. Topographic patterns of the ISS (for each of the 120 pairs of EEG derivations) with the ISS stochastic level for the controland test groups. Because the ISS stochastic level was virtually the same in both groups, it is given only for the control group.Abscissa, ordinal numbers of the derivation pairs; ordinate, ISS. Thick line, ISS in the test group; thin line, ISS in the control group;dashed line, experimentally determined maximum and minimum stochastic levels of the ISS. Asterisks indicate the pairs of leadsin which the differences in ISS between the control and the test groups were significant (the Mann–Whitney U-test) at (*) P < 0.05,(**) P < 0.01, and (***) P < 0.001.The topographic distribution of the derivation pairswith the ISS exceeding the stochastic level was ana-lyzed for three ranges of interelectrode distance (0.48–0.67, 0.79–0.95, and 1.14–1.39) in both the control andthe test groups (Figs. 3a–3c, respectively). The inter-electrode distances were calculated using three-dimen-sional coordinates for each of the derivations [30, 31].As can be seen from Fig. 3, the ISS exceeded thestochastic level in the same derivation pairs for the con-trol group as for the test group. However, there wereanother ten pairs in which the ISS exceeded the sto-chastic level in the control but not in the test group.It was found that, in the control group, the pairs ofEEG derivations with the above-threshold ISS weremostly observed for a large interelectrode distance(Fig. 3c) and rarely for the minimum interelectrode dis-tance (Fig. 3a).Analysis of the percentage of these pairs in both thecontrol and the test groups (table) showed that the pairsof EEG channels with the above-threshold ISS in thetest group, when compared to those in the controlgroup, demonstrated a trend towards a distance-depen-dent redistribution so that the percentage of such pairsincreased in the case of minimum interelectrode dis-tances and decreased in the case of maximum interelec-trode distances. Compared with the control group, thetest group demonstrated a decrease predominantly indistant structural synchrony. This was true mainly forPercentage of the pairs of derivations (for different ranges ofinterelectrode distance) with the ISS exceeding the stochasticlevel in the control and test groupsGroupRange of interelectrode distanceTotal pairs0.48–0.670.79–0.951.14–1.39Healthyadolescents50.0%30.8%19.2%52Schizo-phrenicadolescents57.1%31.0%11.9% 42

Page 4

258HUMAN PHYSIOLOGY Vol. 31 No. 3 2005BORISOV et al.the left fronto–temporal diagonal and bilateral asym-metrical connections (Fig. 3).Along with the topographic analysis of the deriva-tion pairs with ISS values exceeding the threshold inboth the control and the test groups, we compared theISSs of individual pairs between the groups. The ISSswere compared only for the derivation pairs in whichthe value exceeded the threshold in at least one of thetwo groups. The pairs of derivations with significantdifferences in the ISS between the control and the testgroups are represented in Fig. 4.The ISS was lower in the test group for almost allsuch pairs of derivations (except O2–T6). In addition tothe pairs represented in Fig. 2, this was true for bilateralsymmetrical (O1–O2, P3–P4, C3–C4, and F3–F4), pre-dominantly right parietocentral (Pz–P4, Pz–C4, P4–C4,Cz–C4, and C3–P4), predominantly left temporal(T3−T5, T3–C3, and T4–T6), and left prefrontal (F3–Cz)pairs of EEG derivations.DISCUSSIONThe results of spectral and correlation analyses ofthe interaction between different parts of the brain inschizophrenia may lead to conflicting conclusions.Some researchers have reported an increase in EEGcoherence in schizophrenia at rest [6, 32–34] and dur-ing solving cognitive tasks [14]. In other studies involv-ing the same frequency ranges and functional states,either quite opposite effects were observed [7, 8, 35,36] or virtually no significant differences in EEGcoherence were found between patients and controlsubjects [37].Conceivably, such a variety of estimations of EEGcoherence in schizophrenia might be caused by the lackof uniform standards for the organization of such stud-ies with respect to test paradigms, EEG frequencies,and stages of the schizophrenic process [7, 38].Application of new techniques for studying cortico-cortical interactions also contributes to the variety ofconclusions. One such example is [17], where coher-ence analysis and analysis of coincidences of peak fre-quencies in pairs of EEG derivations were performedwith the same samples of healthy subjects and schizo-phrenics. It was found that the topography and thechanges in correlations between EEG parametersdepend not only on the method applied but also onwhether positive or negative symptoms are observed inschizophrenics [39], as well as on the frequency rangesand particular pairs of EEG derivations used in the testprocedures [39]. Entropic analysis of the EEG (mutualinformation analysis), which reports the mutual order-liness of distributions of temporal series, showed a vari-F8O1O2T5T6T4T3F7F3F4C3CzC4P3PzP4F8O1O2T5T6T4T3F7F3F4C3CzC4P3PzP4F8O1O2T5T6T4T3F7F3F4C3CzC4P3PzP4(a)(b)(c)Fig. 3. Topographic distribution of the pairs of derivations with interelectrode distances in the ranges (a) 0.48–0.67, (b) 0.79–0.95,and (c) 1.14–1.39 and the ISS exceeding the stochastic level. Thick line, pairs of derivations with the ISS exceeding the stochasticlevel only in the control group; thin line, pairs of derivations with the ISS exceeding the stochastic level in both groups.F8O1O2T5T6T4T3F7F3F4C3CzC4P3PzP4Fig. 4. Topographic distribution of the pairs of derivationsin which the differences in the ISS between the control andthe test groups were significant (P < 0.05, P < 0.01, and P <0.01). Solid line: the ISS is higher in the control group; dot-ted line: the ISS is higher in the test group.

Page 5

HUMAN PHYSIOLOGY Vol. 31 No. 3 2005ANALYSIS OF EEG STRUCTURAL SYNCHRONY IN ADOLESCENTS259ety of changes in information transmission betweendifferent cortical areas in schizophrenics [18]. Detec-tion of specific nonlinear interdependences throughmutual prediction [40] led to the conclusion that the dif-ference between healthy and schizophrenic subjectsconcerns the topography of interactions between differ-ent cortical areas rather than the direction of changes inEEG synchronization or their dependence on particularpairs of derivations [9].Summarizing the above data, we may argue thatschizophrenia is associated with a variety of changes intypes of mutual determination in pairs of different EEGderivations.In this work, we were the first to obtain data on thechanges in EEG structural synchrony in schizophrenicdisorders. The specific feature of the method we usedfor estimating cortical integration is that it describes theEEG patterns represented by quasi-stationary segmentsrather than particular peaks or waves of the EEG signal[20, 21].Our results are generally consistent with the data onconsiderable changes in corticocortical interrelation-ships in schizophrenia that were reported in other stud-ies.The topographic analysis of the derivation pairswith a decreased structural synchrony in the test groupcompared to the control group and of the pairs with theISS exceeding the threshold only in the control grouprevealed a decrease in structural synchrony between thehemispheres (the O1–O2, P3–P4, and C3–C4, F3–F4 pairsof bilateral symmetrical derivations and the P3–C4, C3–P4, F3–C4, F3–F8, and F7–F4 pairs); in the temporalregions of both hemispheres, predominantly on the left(T5–T3, T5–C3, T5–F7, T6–T4, and T6–C4); in the frontalregions, predominantly on the left (F3–F8, F7–F4, F3–F4, F3–Cz, F3–C4, and T5–F7); and in the right parieto-central region (Pz–P4, Pz–C4, Cz–P4, P4–C4, and Cz–C4).Interestingly, the largest number of derivation pairswith the ISS lower than the stochastic level in the testgroup and higher than this level in the control groupwere observed for the pairs with the maximum distancebetween the electrodes. This suggests a disruption offunctional interdependence between rather distantregions in the test group, although the percentage ofsuch interdependences in adjacent regions was evenhigher than in the control group.Our findings concerning the topographic distribu-tion of the derivation pairs with structural synchronylower in the test than in the control group are consistentto some extent with data obtained using other tech-niques for EEG synchrony in different regions of thebrain in schizophrenic patients.Thus, a decrease in the functional hemispheric inter-dependence in schizophrenia was revealed by the anal-ysis of EEG coherence and β-range synchronization [8]and EEG cross-correlation analysis [41]. A decrease inEEG synchronization in the frontal and central regions,predominantly on the left, was also reported for schizo-phrenics [41]. A decrease in coherence in the ∆, θ, andα ranges was detected in the left frontal region [7].Analysis of nonlinear interdependences showed thatthe EEG difference between schizophrenics andhealthy subjects is most pronounced in the left intra-hemispheric regions [9]. Auto mutual information anal-ysis and mutual information transmission measure(CMI analysis) of the EEG in schizophrenic patientsrevealed a functional deficit of the left temporal lobeand increased interhemispheric information transmis-sion in the temporal lobe [18].Topographically, our findings on a decrease in EEGstructural synchrony in the adolescents with schizo-phrenic disorders are consistent to some extent withpublished data on the changes in functional interdepen-dences between different regions of the brain in schizo-phrenia. However, fundamental differences in themethods used for estimating EEG spatial synchronycan produce unequal results; therefore, one must becareful when comparing these results either with eachother or with our findings.What is the physiological significance of thedetected decrease in EEG structural synchrony in ado-lescents with schizophrenic disorders? The phasicstructure of the EEG, specifically, of the α range,reflects the dynamic changes in cortical neuronalensembles [24, 25], while the ISS is used to estimatethe temporal synchrony of cortical activity of differentregions of the brain with regard to the dynamic changesin local neuronal ensembles. A significant simultaneousintegration (or disintegration) of such assemblies in dis-tant cortical regions may be regarded as spatiotemporalsynchronization of local cortical processes [20, 21, 42].Thus, the decrease in the ISS detected for manypairs of derivations in the schizophrenic adolescentsmay provide evidence for disintegration of operationalcortical activity.In our previous study [28], we examined EEG seg-ments of α activity in the same adolescents. Accordingto our results, the EEG α activity in adolescents withschizophrenic disorders significantly differs from thatin healthy adolescents. In our opinion, these differencespoint to lesser integration of cortical neurons via localsynchronization of their activity in adolescents withschizophrenic disorders as compared to control sub-jects. Even when such synchronization occurs, it is of alesser duration and is less stable. On the strength ofthese data, we assumed that a disintegration trend istypical of the whole neuronal substrate at all levelsfrom local neuronal ensembles to spatially distant neu-ronal networks, causing serious disturbance of interde-pendences in schizophrenia.The results of this study support the above assump-tion and show that this disease is associated not onlywith alteration of local synchronization mechanismsbut also with dramatic impairment of intercortical con-nections, spatiotemporal disintegration being greaterbetween distant regions.